Platform to provide supplemental media content based on content of a media stream and a user accessing the media stream

1. A method, comprising: detecting, by a device, that a user device is receiving a media stream associated with a vehicle, wherein the user device is associated with a user account of a user; receiving, by the device, activity data associated with the user account, and wherein the activity data relates to online activity involving the vehicle; determining, by the device, a characteristic of the user based on the activity data; identifying, by the device, media content of the media stream, wherein the media content includes media that is being provided, via a user interface of the user device, and that is associated with the vehicle; performing, by the device and based on detecting that the user device is receiving the media stream, a search of a database that stores feature information for the vehicle, the search being based on the characteristic of the user; receiving, by the device and based on the search, at least one search result specifying a feature of the vehicle that corresponds to the characteristic of the user; determining, by the device, that the feature is in the media content, obtaining, by the device, feature content associated with the feature based on feature information associated with the feature, wherein the feature information is stored in a data structure that includes information associated with the vehicle; and determining, by the device and for the feature content, a location within a field of view of the media stream, the field of view of the media stream providing a view of the feature; and inserting, by the device, within the media stream, and while the feature is within the field of view of the media stream, the feature content at the location within the field of view of the media stream.

2. The method of claim 1 , further comprising: determining, based on the characteristic of the user and based on a machine learning model, that the user has a threshold level of interest in the feature of the vehicle, wherein the machine learning model has been trained based on at least one of: historical data associated with past online activity of the user; or historical data associated with past online activity of one or more other users.

3. The method of claim 1 , wherein determining that the feature is in the media content comprises: performing an image processing technique on the media content using a feature recognition model, wherein the feature recognition model comprises a machine learning model that has been trained based on at least one of: historical data associated with recognizing the feature in other media content that is associated with the vehicle, historical data associated with recognizing the feature in other media content that is associated with other vehicles, or historical data associated with recognizing, in other media content that is associated with other vehicles, other features that are related to the feature.

4. The method of claim 1 , wherein the media stream comprises a multi-view image stream and determining that the feature is in the media content comprises: obtaining, from the user device, a user input associated with displaying an image of the feature within the media content, wherein the user input indicates a view of the vehicle, wherein the view is one of a plurality of views of the vehicle that are capable of being selected from the multi-view image stream; and determining, from the information associated with the vehicle and the view of the vehicle, that the media content includes the image of the feature.

5. The method of claim 1 , wherein obtaining the feature content comprises: obtaining the feature information from the data structure; determining a type of the feature; and generating the feature content based on the type of the feature, wherein the generated feature content is configured to be displayed within the media content in relation to the feature.

6. The method of claim 1 , further comprising: requesting the user to authorize monitoring of the online activity; receiving a user input that authorizes the monitoring of the online activity; and receiving the activity data based on the user input.

7. The method of claim 1 , wherein inserting the feature content comprises: embedding the feature content into the media content, wherein the embedded feature content is configured to be displayed in a fixed position within the media content in relation to the feature when the user device displays, via the user interface, the feature within the media content.

8. A device, comprising: one or more memories; and one or more processors, communicatively coupled to the one or more memories, configured to: detect that a user device is receiving a media stream associated with a vehicle, wherein the user device is associated with a user account of a user; receive activity data associated with the user account, and wherein the activity data relates to online activity involving the vehicle; determine a characteristic of the user based on the activity data; identify media content of the media stream, wherein the media content includes media that is being provided, via a user interface of the user device, and that is associated with the vehicle; perform, based on detecting that the user device is receiving the media stream, a search of a database that stores feature information for the vehicle, the search being based on the characteristic of the user; receive, based on the search, at least one search result specifying a feature of the vehicle that corresponds to the characteristic of the user; determine that the feature is in the media content; obtain feature content associated with the feature based on feature information associated with the feature, wherein the feature information is stored in a data structure that includes information associated with the vehicle; and determine, for the feature content, a location within a field of view of the media stream, the field of view of the media stream providing a view of the feature; and insert, within the media stream and while the feature is within the field of view of the media stream, the feature content at the location within the field of view of the media stream.

9. The device of claim 8 , wherein the one or more processors are further configured to: determine, based on the characteristic of the user and based on a machine learning model, that the user has a threshold level of interest in the feature of the vehicle, wherein the machine learning model has been trained based on at least one of: historical data associated with past online activity of the user; or historical data associated with past online activity of one or more other users.

10. The device of claim 8 , wherein the one or more processors, when determining that the feature is in the media content, are configured to: perform an image processing technique on the media content using a feature recognition model, wherein the feature recognition model comprises a machine learning model that has been trained based on at least one of: historical data associated with recognizing the feature in other media content that is associated with the vehicle, historical data associated with recognizing the feature in other media content that is associated with other vehicles, or historical data associated with recognizing, in other media content that is associated with other vehicles, other features that are related to the feature.

11. The device of claim 8 , wherein the media stream comprises a multi-view image stream and the one or more processors, when determining that the feature is in the media content, are configured to: obtain, from the user device, a user input associated with displaying an image of the feature within the media content, wherein the user input indicates a view of the vehicle, wherein the view is one of a plurality of views of the vehicle that are capable of being selected from the multi-view image stream; and determine, from the information associated with the vehicle and the view of the vehicle, that the media content includes the image of the feature.

12. The device of claim 8 , wherein the one or more processors, when obtaining the feature content, are configured to: obtain the feature information from the data structure; determine a type of the feature; and generate the feature content based on the type of the feature, wherein the generated feature content is configured to be displayed within the media content in relation to the feature.

13. The device of claim 8 , wherein the one or more processors are further configured to: request the user to authorize monitoring of the online activity; receive a user input that authorizes the monitoring of the online activity; and receive the activity data based on the user input.

14. The device of claim 8 , wherein the one or more processors, when inserting the feature content, are configured to: embed the feature content into the media content, wherein the embedded feature content is configured to be displayed in a fixed position within the media content in relation to the feature when the user device displays, via the user interface, the feature within the media content.

15. A non-transitory computer-readable medium storing one or more instructions that, when executed by one or more processors, cause the one or more processors to: detect that a user device is receiving a media stream associated with a vehicle, wherein the user device is associated with a user account of a user; receive activity data associated with the user account, wherein the activity data relates to online activity involving the vehicle; determine a characteristic of the user based on the activity data; identify media content of the media stream, wherein the media content includes media that is being provided, via a user interface of the user device, and that is associated with the vehicle; perform, based on detecting that the user device is receiving the media stream, a search of a database that stores feature information for the vehicle, the search being based on the characteristic of the user; receive, based on the search, at least one search result specifying a feature of the vehicle that corresponds to the characteristic of the user; determine that the feature is in the media content; obtain feature content associated with the feature based on feature information associated with the feature, wherein the feature information is stored in a data structure that includes information associated with the vehicle; and determine, for the feature content, a location within a field of view of the media stream, the field of view of the media stream providing a view of the feature; and insert, within the media stream and while the feature is within the field of view of the media stream, the feature content at the location within the field of view of the media stream.

16. The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions, when executed by the one or more instructions, further cause the one or more processors to: determine, based on the characteristic of the user and based on a machine learning model, that the user has a threshold level of interest in the feature of the vehicle, wherein the machine learning model has been trained based on at least one of: historical data associated with past online activity of the user; or historical data associated with past online activity of one or more other users.

17. The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions, that cause the one or more processors to determine that the feature is in the media content, cause the one or more processors to: perform an image processing technique on the media content using a feature recognition model, wherein the feature recognition model comprises a machine learning model that has been trained based on at least one of: historical data associated with recognizing the feature in other media content that is associated with the vehicle, historical data associated with recognizing the feature in other media content that is associated with other vehicles, or historical data associated with recognizing, in other media content that is associated with other vehicles, other features that are related to the feature.

18. The non-transitory computer-readable medium of claim 15 , wherein the media stream comprises a multi-view image stream and the one or more instructions, that cause the one or more processors to determine that the feature is in the media content, cause the one or more processors to: obtain, from the user device, a user input associated with displaying an image of the feature within the media content, wherein the user input indicates a view of the vehicle, wherein the view is one of a plurality of views of the vehicle that are capable of being selected from the multi-view image stream; and determine, from the information associated with the vehicle and the view of the vehicle, that the media content includes the image of the feature.

19. The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions, that cause the one or more processors to obtain the feature content, further cause the one or more processors to: obtain the feature information from the data structure; determine a type of the feature; and generate the feature content based on the type of the feature, wherein the generated feature content is configured to be displayed within the media content in relation to the feature.

20. The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions, when executed by the one or more instructions, further cause the one or more processors to: request the user to authorize monitoring of the online activity; receive a user input that authorizes the monitoring of the online activity; and receive the activity data based on the user input.